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Data Concepts in Azure Machine Learning

2023-08-14T03:18:24+00:00

Azure Machine Learning Data Concepts URI A Uniform Resource Identifier (URI) represents a storage location on a local computer, Azure storage, or a publicly available http(s) location. URIs can be used as inputs or outputs to an Azure Machine Learning job and can be mapped to the compute target filesystem in different modes: read-only mount, read-write mount, download, or upload. URIs use identity-based authentication to connect to storage services, with options for Azure Active Directory ID or Managed Identity. Data types Azure Machine Learning supports three data types: File, Folder, and Table. File: References a single file and can have [...]

Data Concepts in Azure Machine Learning2023-08-14T03:18:24+00:00

Azure Machine Learning

2023-03-20T03:22:05+00:00

Azure Machine Learning Cheat Sheet A service to train, deploy, automate, manage, and track machine learning models. Azure ML offers Basic and Enterprise editions. You can use Azure ML SDK for Python, Azure ML Studio, and ML CLI to manage your deployed models. You can automate and accelerate the ML lifecycle using MLOps. Azure ML designer allows you to visually connect (drag-and-drop) datasets and modules without writing any code. ML pipelines provide a complete logical workflow and an ordered sequence of steps. AutoML uses the target metric you specify to train and tune a model. Azure Cognitive Services enables developers [...]

Azure Machine Learning2023-03-20T03:22:05+00:00

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